[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread asfgit
Github user asfgit closed the pull request at:

https://github.com/apache/spark/pull/22638


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[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread dilipbiswal
Github user dilipbiswal commented on a diff in the pull request:

https://github.com/apache/spark/pull/22638#discussion_r222957505
  
--- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala ---
@@ -127,16 +127,16 @@ class DatasetCacheSuite extends QueryTest with 
SharedSQLContext with TimeLimits
   }
 
   test("cache UDF result correctly") {
-val expensiveUDF = udf({x: Int => Thread.sleep(5000); x})
-val df = spark.range(0, 10).toDF("a").withColumn("b", 
expensiveUDF($"a"))
+val expensiveUDF = udf({x: Int => Thread.sleep(2000); x})
--- End diff --

@mgaido91 Thanks marco.


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[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread mgaido91
Github user mgaido91 commented on a diff in the pull request:

https://github.com/apache/spark/pull/22638#discussion_r222952924
  
--- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala ---
@@ -127,16 +127,16 @@ class DatasetCacheSuite extends QueryTest with 
SharedSQLContext with TimeLimits
   }
 
   test("cache UDF result correctly") {
-val expensiveUDF = udf({x: Int => Thread.sleep(5000); x})
-val df = spark.range(0, 10).toDF("a").withColumn("b", 
expensiveUDF($"a"))
+val expensiveUDF = udf({x: Int => Thread.sleep(2000); x})
--- End diff --

well, I do think this will pass 100% times, my concern was that in case of 
a regression we might fail detecting it. But yes, with the repartition to 1 
you're right, I haven't considered it, otherwise they may have run in parallel. 
So this seems enough.


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[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread dilipbiswal
Github user dilipbiswal commented on a diff in the pull request:

https://github.com/apache/spark/pull/22638#discussion_r222946564
  
--- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala ---
@@ -127,16 +127,16 @@ class DatasetCacheSuite extends QueryTest with 
SharedSQLContext with TimeLimits
   }
 
   test("cache UDF result correctly") {
-val expensiveUDF = udf({x: Int => Thread.sleep(5000); x})
-val df = spark.range(0, 10).toDF("a").withColumn("b", 
expensiveUDF($"a"))
+val expensiveUDF = udf({x: Int => Thread.sleep(2000); x})
--- End diff --

@mgaido91 OK, please correct me on this one. So we insert 2 rows .. i.e two 
invocation of the UDF amounting to 2 * 2sec  = 4 secs of execution. So wouldn't 
a 2 sec fail time be ok ?


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[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread mgaido91
Github user mgaido91 commented on a diff in the pull request:

https://github.com/apache/spark/pull/22638#discussion_r222945036
  
--- Diff: 
sql/core/src/test/scala/org/apache/spark/sql/DatasetCacheSuite.scala ---
@@ -127,16 +127,16 @@ class DatasetCacheSuite extends QueryTest with 
SharedSQLContext with TimeLimits
   }
 
   test("cache UDF result correctly") {
-val expensiveUDF = udf({x: Int => Thread.sleep(5000); x})
-val df = spark.range(0, 10).toDF("a").withColumn("b", 
expensiveUDF($"a"))
+val expensiveUDF = udf({x: Int => Thread.sleep(2000); x})
--- End diff --

mmh...since we fail after 2 seconds we may pass this even in case it 
doesn't work. Shall we put it to 3? or 2500 at least?


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[GitHub] spark pull request #22638: [SPARK-25610][SQL][TEST] Improve execution time o...

2018-10-05 Thread dilipbiswal
GitHub user dilipbiswal opened a pull request:

https://github.com/apache/spark/pull/22638

[SPARK-25610][SQL][TEST] Improve execution time of DatasetCacheSuite: cache 
UDF result correctly

## What changes were proposed in this pull request?
In this test case, we are verifying that the result of an UDF  is cached 
when the underlying data frame is cached and that the udf is not evaluated 
again when the cached data frame is used.

To reduce the runtime we do : 
1) Use a single partition dataframe, so the total execution time of UDF is 
more deterministic.
2) Cut down the size of the dataframe from 10 to 2.
3) Reduce the sleep time in the UDF from 5secs to 2secs.
4) Reduce the failafter condition from 3 to 2.

With the above change, it takes about 4 secs to cache the first dataframe. 
And subsequent check takes a few hundred milliseconds.
The new runtime for 5 consecutive runs of this test is as follows : 
```
[info] - cache UDF result correctly (4 seconds, 906 milliseconds)
[info] - cache UDF result correctly (4 seconds, 281 milliseconds)
[info] - cache UDF result correctly (4 seconds, 288 milliseconds)
[info] - cache UDF result correctly (4 seconds, 355 milliseconds)
[info] - cache UDF result correctly (4 seconds, 280 milliseconds)
```
## How was this patch tested?
This is s test fix.

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/dilipbiswal/spark SPARK-25610

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/22638.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #22638


commit 97d18feeb8713da42b9f97d2343063bac1cba4b6
Author: Dilip Biswal 
Date:   2018-10-05T07:51:35Z

[SPARK-25610][TEST] Improve execution time of DatasetCacheSuite: cache UDF 
result correctly




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